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Call Number: NRLF SF601 .AS;NRLF SF601 .AS Format: Article Printed Ext. No: [NLM PMID] 4008297
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Title: Journal of the American Veterinary Medical Association Article Author: Hart, B L Article Title: Selecting pet dogs on the basis, of cluster analysis of breed behavior profiles and gender. Volume/Issue: 186( 11) Part Pub. Date: 1985-06 Publisher: [American Veterinary Medical Association]/lthaca, N.Y.
Pages: 1181-5 Pub. Place: Ithaca, N.Y. Borrower: UCD Health Science Library
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close, as illustrated in Figure 1. In reality, each factor contributes to virtually all traits, but is expressed primarily in just a few traits. Therefore, the factor rank envelope does not necessarily closely follow the ranks for each trait. The factor analysis does reveal that rankings on some traits are correlated with others. Breeds that are high on 1 form of aggression tend to be high on other forms of aggression. Obviously, one obtains more specific information about a No. Authorities ranking males higher - No. Authorities breed's reputed performance on a particular trait by ranking females higher -o- Total No. Authorities x 100 looking at the trait rather than the factor to which the trait is assigned. If all authorities ranked male dogs higher than females, the score for males would be 100. The degree to which some Cluster analysis- The aim was to perform the authorities would state there is no difference between cluster analysis to group dog breeds according to a males and females limits the quantitative difference befew underlying factors representing behavioral pretween males and females even though 1 gender or the other was ranked predominantly higher for authorities that dispositions. Therefore, only the 3 factors that accounted for 81% of the variance were utilized. The chose 1 gender over the other. within-covariance analysis appeared to segregate breeds most clearly according to the visual appearResults and Discussion ance of the 2-dimensional matrix display. A separate Factor analysis- The percentage of variance ac- cluster. analysis was performed each time for 4 counted for by principal components 1 through 5 was through 8 clusters of breeds, using the scores on each 43%, 24%, 14%, 7%, and 3%, respectively. Thus, 3 of the 3 main factors. principal components accounted for 81% of the variFor each analysis, the mean decile ranking of each ance, and 4 principal components for 88%. The breed for each of the 3 factors and the standard errors increments in cumulative variance accounted for were determined. The relative magnitude of the stanbeyond the 4 principal components was judged small dard errors of the clusters was an indication of the enough to limit the analysis to 4. After rotation, each uniformity of each cluster. Considering the magniof the 13 behavioral traits was assigned to 1 of the 4 tude of the standard errors, it was evident that groups factors according to the highest factor score coeffi- in the 7-cluster analysis were as uniform as in the 6cient on each factor. In Table 1 the traits are listed cluster analysis, and considerably more uniform under each factor in order of decreasing loading on than in the 8-cluster analysis. From the visual the factor to which they were assigned. display, the 7-cluster analysis also was noticeably Descriptive labels that appeared to represent a more segregated than the 8-cluster analysis. Therecommon element in most or all of the traits listed fore, it was decided that the 7-cluster analysis was the under each factor were assigned to factors 1, 2, and 3. most appropriate for clustering of breeds on the basis These were reactivity, aggressiveness, and train- of similarity in the factors of reactivity, aggression, ability (Table 1). The factor for destructiveness and and trainability. playfulness was not given a descriptive label. Each To quantitate the general behavioral characterisbreed was then given a score for each of the 4 factors tics of each of the 7 clusters, mean decile ranks of and assigned a rank of 1 through 56 in order of breeds within each group for each factor were desigincreasing scores. By then dividing breeds into nated as very low (1 to 2.5), low (2.6 to 4.0), medium deciles, as was done for ranking of each trait previ- (4.1 to 7.0), high (7.1 to 8.5), or very high (8.6 to 10). ously,4 a profile of factor characteristics was obtained Table 2 presents the abbreviated description of each for each breed. Figure 1 illustrates the use of factor cluster and the breeds grouped together according to score envelopes to express the profile in conjunction the cluster analysis program. with the profile of the 13 traits, as reported elseSince the characteristics listed for each cluster where.4 were based on mean decile scores of all breeds in the The correspondence between decile rankings on group, the descriptors actually defined the cluster in characteristics and factor scores usually was quite a general sense. In the computer analysis, breeds 1182
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